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1- I agree that speed is intelligence[+], but you're suggesting we can reduce accuracy, increase speed, and get better results. I don't buy it.

2- I'm confused. Claude Code and a Neovim plugin I used both do edits/diffs. Are you saying they're actually rewriting entire files instead?

3- Aren't "simple tasks" just things you train the model on? If so, are you solving a bunch of simple tasks or offering custom training?

> No more slow full-file rewrites or brittle search-and-replace hacks.

Here's the thing - LLMs are already blazing fast. I commented the other day that you could probably write Chrome's entire code base in a couple months at average speed. The bottleneck isn't speed, it's accuracy; that's of course my opinion.

+: https://omarabid.com/claude-magic






Accuracy of course comes first - errors of any sort break flow state and are massively disruptive. Claude Code does search and replace. The failure rate of search and replace is rather high (over 11%) but claude can self correct them. Fast Apply is more accurate than search and replace. Full file rewrites for files under 10k tokens can work quite well - like 98%+ but its absurdly expensive and slow. Fast Apply is a much better option that balances speed and accuracy

I'm having trouble getting your platform to work properly. When I tried the examples you provided, I couldn't understand what they were supposed to demonstrate. The code I wrote either breaks or just outputs your sample code instead of working correctly. My usage dashboard shows 0, so I can't tell if the platform is actually functioning. The only thing that seems to work is the payment redirect to Stripe.

I think you need to take a step back and contemplate.




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